A graph-based proactive fault identification approach in computer networks

Authors:
Yijiao Yu;Qin Liu;Liansheng Tan
Affiliations:
Department of Computer Science, Central China Normal University, Wuhan 430079, China;Department of Computer Science, Central China Normal University, Wuhan 430079, China;Department of Computer Science, Central China Normal University, Wuhan 430079, China
Venue:
Computer Communications
Year:
2005

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Abstract

In large-scale computer networks, the isolation of the primary failure source is a challenging task. This article presents a proactive network fault diagnosis approach based on graph theory. Compared with other approaches, the manager of network management system checks the status of the managed devices actively rather than receive messages from those objects passively. The salient feature of this approach is that the possible failure sources, including the real one, can be computed precisely and quickly without any alarm historical information or strict assumptions. This approach does not introduce much processing complexity by taking full use of matrix and Boolean operations. To test and evaluate our proposed algorithm, it is implemented in Java and tested in a real large network environment. The experiment results show that this approach is not only efficient but also scalable on fault identification in large-scale computer networks.